The use of Bayesian networks for realist evaluation of complex interventions: evidence for prevention of human trafficking

Ligia Kiss,Cathy Zimmerman,Joelle Mak,Alys Mcalpine,David Fotheringhame

doi:10.1007/s42001-020-00067-8

Ligia Kiss, Cathy Zimmerman + Show 3 more

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https://doi.org/10.1007/s42001-020-00067-8

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Abstract

Complex systems and realist evaluation offer promising approaches for evaluating social interventions. These approaches take into account the complex interplay among factors to produce outcomes, instead of attempting to isolate single causes of observed effects. This paper explores the use of Bayesian networks (BNs) in realist evaluation of interventions to prevent complex social problems. It draws on the example of the theory-based evaluation of the Work in Freedom Programme (WIF), a large UK-funded anti-trafficking intervention by the International Labour Organisation in South Asia. We used BN to explore causal pathways to human trafficking using data from 519 Nepalese returnee migrants. The findings suggest that risks of trafficking are mostly determined by migrants’ destination country, how they are recruited and in which sector they work. These findings challenge widely held assumptions about individual-level vulnerability and emphasize that future investments will benefit from approaches that recognise the complexity of an intervention’s causal mechanisms in social contexts. BNs are a useful approach for the conceptualisation, design and evaluation of complex social interventions.

Highlights

Realist evaluation of complex social systemsFailing to appreciate complex causal relationships in social interventions has often led to misinterpretations, over simplication or even harm [1,2,3,4]
This paper explores the use of Bayesian networks (BNs) in realist evaluation of interventions to prevent complex social problems
In each district, implementing partners selected 6 Village Department Committees (VDCs), the smaller administrative unit in Nepal, where intervention activities could be delayed until the fieldwork was completed

Summary

Introduction

Realist evaluation of complex social systemsFailing to appreciate complex causal relationships in social interventions has often led to misinterpretations, over simplication or even harm [1,2,3,4]. New conceptual and methodological approaches offer promising alternatives for the evaluation of complex social interventions [5,6,7]. Over the past two decades, calls for research that respond to the challenges of explaining and evaluating complex systems have abounded both in Public Health and the Social Sciences [6,7,8,9,10,11,12]. Theories on complex adaptive systems have been increasingly used to understand social phenomena, and a trend in theory-based and realist evaluation has been gaining momentum [13, 14]. Realist evaluations focus on programme theories to examine the validity of assumptions and ideas underlying how, why and under which circumstances complex social interventions work [15]

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